Translation of digital phenotypic traits: fromimage to commercial relevance

Translation of digital phenotypic traits: from image to commercial relevance

Dr. Shital Dixit PAG XXI 15th Jan 2013

Presentation outline • Challenges in plant phenotyping • Facility of PhenoFab®

• Novelty of PhenoFab® projects • Case study: Correlating early digital traits to later yield related traits • Conclusions

Shital Dixit

15-01-2013

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Challenges in plant phenotyping Cold

Salt

Drought

• • •

Objective phenotyping Digital Phenotyping High-throughput

Abiotic agents

Biotic agents

Subjective/bias scoring Shital Dixit

15-01-2013

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Digital Phenotyping

Objective data collection from digital images to measure morphological and physiological characteristics through image analysis is known as digital phenotyping

Shital Dixit

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PhenoFab® – the facility

3D Conveyor Scanalyzer

•Greenhouse setup with climate control •Moving pots/trays: capacity: 1040 pots

•GMO authorized Shital Dixit

15-01-2013

Slide 5

3D Image stations Capacity: Plant Height 2.6 mts.

Visible light -Shape - Color

NIR - internal structure - Water content

Fluorescence -Chlorophyll analysis

Shital Dixit

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Slide 6

Novelty of PhenoFab facility

Agri Food Biotech company

Automation of scientific images

Software/hardware development

Value creation for Customer

Traits/genes/genomics/bioinformatic/data analysis

Shital Dixit

15-01-2013

Slide 7

Drought, WUE Cotton Tobacco

NUE Root phenotyping Flowering time Crop architechture Height, width Canopy structure Heavy metal toxicity Effect of growth substrate Crop growth rate Cabbage Fruit shape, color and Taraxacum shelf life

Tomato-roots

Pepper

Sorghum

Maize

Miscanthus

Canola

Rice

Ficus

Sugarbeet

Grass

Wheat

Tomato

Cabbage

Shital Dixit

Cucumber

15-012013

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Root imaging using PhenoFab

• Shoot/root ratio • Effects of stress  Drought  Salt  Heat  nutrition

Digital detection of roots by the algorithm

Slide 9

Root imaging using PhenoFab Direct root mass measurement

PhenoFab root measurement

93 % Correlation !

PhenoFab root measurement

Direct root mass measurement 93 % Correlation !

Shital Dixit

15-012013

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PhenoFab 速 project workflow

Idea

PhenoFab 速

to workplan

5 weeks

From image to digital phenotyping

Statistical correlation study

Conclusions

4 months Shital Dixit

15-01-2013

Slide 11

PhenoFab project deliverables • Pixel count RGB • Growth curves • Growth model • Project report • Full database • 4 sides + top growth movies • RGB • NIR • Fluo • Overall impression images Shital Dixit

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Slide 12

c

Project report

Poster no. PO165

KeyGene booth 111 Shital Dixit

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Slide 13

Role of digital phenotypes in predicting later yield related traits in crops

From image to digital phenotyping

Later crop trait

Early crop trait Shital Dixit

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Case study: Correlating early digital traits to later yield traits in tomato Experimental Set-up PhenoFab 30 genotypes 5 replicates 5 weeks

Breeders/commercial greenhouse 30 genotypes Two greenhouse locations

Early crop trait

Later crop trait Shital Dixit

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Case study: Correlating early digital traits to later yield traits in tomato Early crop trait Digital phenotype data •Breeding values •Daily averages •Growth parameters

Later crop trait

Later “yield-related” traits •Fruit quantity •Fruit yield (kg)

Shital Dixit

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Correlation study using single digital phenotype

• Yield related trait:

Tomato fruit weight

0.4 R-square (-0.63 correlation)

• Single digital phenotype describing plant architecture

Shital Dixit

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Correlation study using single digital phenotype

Digital phenotype

0.4 R-square (-0.63 correlation)

Field tomato fruit weight Shital Dixit

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Correlation study using two digital phenotype • Yield related trait:

Tomato fruit weight

0.57 adj. R square (0.75 multiple correlation)

• Model using two digital phenotypes (describing plant architecture)

Shital Dixit

15-01-2013

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Correlation study using two digital phenotype

Digital phenotype model

0.57 adj. R square (0.75 multiple correlation)

Field tomato fruit weight Shital Dixit of 15-01-2013 20 GmbH PhenoFab速 is a registered trademark Keygene N.V. and Lemnatec

Conclusions  PhenoFab provides HTP, non-destructive shoot and root measurements.  PhenoFab has overcomed data anlaysis challenges for many traits  PhenoFab has succesfully demonstrated example of correlating early digital traits to yield in tomato generating commercial relevance for its client.

Shital Dixit

15-01-2013

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The KeyBox system

Idea

KeyBox data

to workplan

From image to digital phenotyping

Statistic correlation study

Conclusions

KeyGene booth 111 Shital Dixit

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Disease phenotyping Susceptibility Score 25.00%

Percentage

20.00%

15.00%

10.00%

5.00%

0.00% Wt WT

S+mlo

A

D+mlo

B

D

C

T+mlo

D

T

E

Arabidopsis

T

D

E

Resistance group

C B

D

D+mlo S+mlo

WT A

Arabidopsis

T+mlo

Wt 0

2

4

6

8

Fold resistance com pared to Wt

Shital Dixit

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The KeyBoxTM system Fruit quality traits

red area in pixels: 155275 Cracked area in pixels: 3188

red area in pixels: 191589 Cracked area in pixels: 345

red area in pixels: 157381 Cracked area in pixels: 118

red area in pixels: 113847 Cracked area in pixels: 6670

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The KeyBoxTM system Fruit quality traits

Crack: 6892 pixels; 37% Dark spots: 2430 Roundness Deviation: 296

Crack: 84561 pixels;51% Dark spots 1461 Roundness deviation: 25 15-01-2013

The KeyBoxTM system Leaf shape, area, color

15-01-2013

Acknowledgements      

Gert-Jan Speckmann Jose Guerra Koen Huvenaars Marco van Schriek Anker Sørensen Shital Dixit

Martijn van Stee

   

Dirk Vandenhirtz Joerg Vandenhirtz Kevin Nagel Ralph Schunk Shital Dixit

15-01-2013

Slide 27

PhenoFab: The plant phenotyping facility in Europe

Shital Dixit

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Slide 28

The PhenoFab速 facility

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